Networking Fundamentals exam Dumps

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Exam Title : Microsoft Technology Associate (MTA) - Networking Fundamentals
Exam ID : 98-366
Exam Duration : 45 mins
Questions in exam : 40-60
Passing Score : 700 / 1000
Official Training : 40032A: Networking and Security Fundamentals: Training 2-Pack for MTA Exams 98-366 and 98-367 (five days)
40366A: Networking Fundamentals: MTA exam 98-366 (three days)
Exam Center : Pearson VUE
Real Questions : Microsoft Networking Fundamentals Real Questions
VCE practice test : Microsoft 98-366 Certification VCE Practice Test

Understanding network infrastructures (3035%)
Understand the concepts of Internet, intranet, and extranet
Virtual Private Network (VPN), security zones, firewalls
Understand local area networks (LANs)
Perimeter networks; addressing; reserved address ranges for local use (including local loopback IP), VLANs; wired LAN and wireless LAN
Understand wide area networks (WANs)
Leased lines, dial-up, ISDN, VPN, T1, T3, E1, E3, DSL, cable modem, and more, and their characteristics (speed, availability) Understand wireless networking
Types of wireless networking standards and their characteristics (802.11a,b,g,n,ac including different GHz ranges), types of network security (WPA, WEP, 802.1X, and others), point-to-point (P2P) wireless, ad hoc networks, wireless bridging
Understand network topologies and access methods
Star, mesh, ring, bus, logical and physical topologies
Preparation resources

Solution Design Considerations for Network Topologies
Wireless LAN Service Overview
Wired and Wireless Networking with 802.1X Authentication

Understanding network hardware (2025%) Understand switches
Transmission speed, number and type of ports, number of uplinks, speed of uplinks, managed or unmanaged switches, VLAN capabilities, Layer 2 and Layer 3 switches and security options, hardware redundancy, support, backplane speed, switching types and MAC table, understand capabilities of hubs versus switches, virtual switches
Understand routers
Transmission speed considerations, directly connected routes, static routing, dynamic routing (routing protocols), RIP vs. OSPF, default routes; routing table and how it selects best route(s); routing table memory, Network Address Translation (NAT), software routing in Windows Server, installing and configuring routing; Quality of Service (QoS)
Understand media types
Cable types and their characteristics, including media segment length and speed; fiber optic; twisted pair shielded or unshielded; catxx cabling, wireless; susceptibility to external interference (machinery and power cables); susceptibility to electricity (lightning), susceptibility to interception
Preparation resources

Computer Hardware and Windows Server
Routing
Understanding protocols and services (45-50%)
Understand the Open Systems Interconnection (OSI) model
OSI model; Transmission Control Protocol (TCP) model; examples of devices, protocols, applications, and which OSI/TCP layer they belong to; TCP and User Datagram Protocol (UDP); well-known ports for most used purposes (not necessarily Internet); packets and frames
Understand IPv4
Subnetting, IPconfig, why use Internet Protocol version 4 (IPv4), addressing, ipv4toipv6 tunneling protocols to ensure backward compatibility, dual IP stack, subnetmask, gateway, ports, packets, reserved address ranges for local use (including local loopback IP)
Understand IPv6
Subnetting, IPconfig, why use IPv6, addressing, ipv4toipv6 tunneling protocols to ensure backward compatibility, dual IP stack, subnetmask, gateway, ports, packets, reserved address ranges for local use (including local loopback IP)
Understand names resolution
DNS, resource records, Windows Internet Name Service (WINS), steps in the name resolution process, HOSTS file, LMHOSTS file
Understand networking services
Dynamic Host Configuration Protocol (DHCP), Network Address Translation (NAT), firewalls, remote access, VPN
Understand TCP/IP
Tools (such as ping), tracert, pathping, Telnet, IPconfig, netstat, reserved address ranges for local use (including local loopback IP), protocols

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98-366 Networking exam format

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rectangular Wave indicators

It has been discovered that any repeating, non-sinusoidal waveform can also be equated to a mix of DC voltage, sine waves, and/or cosine waves (sine waves with a ninety degree part shift) at a considerable number of amplitudes and frequencies.

here is authentic no be counted how bizarre or convoluted the waveform in question may be. So lengthy as it repeats itself always over time, it's reducible to this series of sinusoidal waves.

In certain, it has been discovered that square waves are mathematically akin to the sum of a sine wave at that same frequency, plus an unlimited series of odd-numerous frequency sine waves at diminishing amplitude:

repeating square wave at 50hz

This certainty about waveforms originally may appear too bizarre to accept as true with. youngsters, if a square wave is in fact an unlimited series of sine wave harmonics introduced together, it stands to intent that we may still be in a position to show this by way of including collectively a couple of sine wave harmonics to supply a close approximation of a rectangular wave.

This reasoning is not handiest sound, but without difficulty validated with SPICE.

The circuit we’ll be simulating is nothing more than several sine wave AC voltage sources of the relevant amplitudes and frequencies linked together in collection. We’ll use SPICE to plot the voltage waveforms across successive additions of voltage sources, like this:

A square wave is approximated by the sum of harmonics.

A square wave is approximated by the sum of harmonics.

during this selected SPICE simulation, I’ve summed the first, 3rd, fifth, 7th, and 9th harmonic voltage sources in sequence for a complete of 5 AC voltage sources. The primary frequency is 50 Hz and each harmonic is, of course, an integer numerous of that frequency.

The amplitude (voltage) figures aren't random numbers; somewhat, they've been arrived at throughout the equations shown within the frequency series (the fraction 4/π multiplied by means of 1, 1/three, 1/5, 1/7, and so forth. for each and every of the expanding peculiar harmonics).

constructing a squarewave v1 1 0 sin (0 1.27324 50 0 0) 1st harmonic (50 Hz) v3 2 1 sin (0 424.413m a hundred and fifty 0 0) third harmonic v5 three 2 sin (0 254.648m 250 0 0) fifth harmonic v7 four 3 sin (0 181.891m 350 0 0) 7th harmonic v9 5 4 sin (0 141.471m 450 0 0) ninth harmonic r1 5 0 10k .tran 1m 20m .plot tran v(1,0) Plot 1st harmonic .plot tran v(2,0) Plot 1st + third harmonics .plot tran v(3,0) Plot 1st + third + 5th harmonics .plot tran v(4,0) Plot 1st + third + fifth + 7th harmonics .plot tran v(5,0) Plot 1st + . . . + 9th harmonics .end

I’ll narrate the analysis step by step from here, explaining what it is we’re looking at. in this first plot, we see the fundamental-frequency sine-wave of 50 Hz by using itself. it is nothing however a pure sine shape, with no further harmonic content. here's the sort of waveform produced by an amazing AC power supply:

Pure 50 Hz sinewave.

Pure 50 Hz sinewave.

next, we see what occurs when this clean and easy waveform is mixed with the third harmonic (thrice 50 Hz, or one hundred fifty Hz). abruptly, it doesn’t seem like a clean sine wave any more:

Sum of 1st (50 Hz) and 3rd (150 Hz) harmonics approximates a 50 Hz square wave.

Sum of 1st (50 Hz) and third (a hundred and fifty Hz) harmonics approximates a 50 Hz rectangular wave.

the upward thrust and fall times between superb and poor cycles are a great deal steeper now, and the crests of the wave are nearer to becoming flat like a squarewave. Watch what happens as we add the subsequent ordinary harmonic frequency:

Sum of 1st, 3rd and 5th harmonics approximates square wave.

Sum of 1st, 3rd and fifth harmonics approximates rectangular wave.

the most noticeable trade here is how the crests of the wave have flattened even more. There are greater a number of dips and crests at every end of the wave, however these dips and crests are smaller in amplitude than they have been earlier than. Watch again as we add the next abnormal harmonic waveform to the mix:

Sum of 1st, 3rd, 5th, and 7th harmonics approximates square wave.

Sum of 1st, 3rd, fifth, and 7th harmonics approximates square wave.

right here we will see the wave fitting flatter at every height. at last, adding the 9th harmonic, the fifth sine wave voltage source in our circuit, we achieve this outcomes:

Sum of 1st, 3rd, 5th, 7th and 9th harmonics approximates square wave.

Sum of 1st, 3rd, 5th, 7th and 9th harmonics approximates square wave.

The culmination of including the first five abnormal harmonic waveforms together (all on the correct amplitudes, of course) is an in depth approximation of a square wave. The factor in doing here is as an example how we will construct a square wave up from varied sine waves at different frequencies, to show that a pure square wave is in reality such as a sequence of sine waves.

When a square wave AC voltage is applied to a circuit with reactive components (capacitors and inductors), these accessories react as if they were being exposed to several sine wave voltages of distinct frequencies, which in fact they are.

The incontrovertible fact that repeating, non-sinusoidal waves are equivalent to a particular sequence of additive DC voltage, sine waves, and/or cosine waves is a final result of how waves work: a fundamental property of all wave-linked phenomena, electrical or in any other case.

The mathematical method of reducing a non-sinusoidal wave into these constituent frequencies is called Fourier analysis, the details of which can be smartly past the scope of this text. youngsters, computer algorithms were created to operate this evaluation at excessive speeds on precise waveforms, and its application in AC energy first-rate and signal analysis is widespread.

SPICE has the capacity to pattern a waveform and in the reduction of it into its constituent sine wave harmonics by way of a Fourier seriously change algorithm, outputting the frequency analysis as a table of numbers. Let’s are attempting this on a rectangular wave, which we already recognize consists of strange-harmonic sine waves:

squarewave evaluation netlist v1 1 0 pulse (-1 1 0 .1m .1m 10m 20m) r1 1 0 10k .tran 1m 40m .plot tran v(1,0) .4 50 v(1,0) .conclusion

the heartbeat choice within the netlist line describing voltage supply v1 instructs SPICE to simulate a rectangular-fashioned “pulse” waveform, during this case one it really is symmetrical (equal time for each half-cycle) and has a top amplitude of 1 volt. First we’ll plot the rectangular wave to be analyzed:

Squarewave for SPICE Fourier analysis

Squarewave for SPICE Fourier evaluation

subsequent, we’ll print the Fourier evaluation generated by SPICE for this rectangular wave:

fourier components of transient response v(1) dc element = -2.439E-02 harmonic frequency fourier normalized phase normalized no (hz) part element (deg) section (deg) 1 5.000E+01 1.274E+00 1.000000 -2.195 0.000 2 1.000E+02 4.892E-02 0.038415 -ninety four.390 -ninety two.195 3 1.500E+02 four.253E-01 0.333987 -6.585 -4.390 four 2.000E+02 four.936E-02 0.038757 -ninety eight.780 -ninety six.585 5 2.500E+02 2.562E-01 0.201179 -10.976 -eight.780 6 3.000E+02 5.010E-02 0.039337 -103.171 -a hundred.976 7 three.500E+02 1.841E-01 0.144549 -15.366 -13.171 eight 4.000E+02 5.116E-02 0.040175 -107.561 -105.366 9 4.500E+02 1.443E-01 0.113316 -19.756 -17.561 complete harmonic distortion = forty three.805747 percent

Plot of Fourier analysis results.

Plot of Fourier analysis outcomes.

here, (determine above) SPICE has damaged the waveform down into a spectrum of sinusoidal frequencies as much as the ninth harmonic, plus a small DC voltage labelled DC element.

I needed to inform SPICE of the fundamental frequency (for a rectangular wave with a 20 millisecond length, this frequency is 50 Hz), so it knew how to classify the harmonics. notice how small the figures are for all of the even harmonics (2nd, 4th, 6th, 8th), and the way the amplitudes of the unusual harmonics shrink (1st is greatest, ninth is smallest).

This equal approach of “Fourier Transformation” is frequently used in computerized vigor instrumentation, sampling the AC waveform(s) and deciding upon the harmonic content thereof. a typical computing device algorithm (sequence of software steps to function a task) for here is the quick Fourier seriously change or FFT characteristic.

You don't need to be anxious with precisely how these laptop routines work, however be privy to their existence and software.

This identical mathematical approach utilized in SPICE to research the harmonic content material of waves will also be applied to the technical analysis of tune: breaking apart any selected sound into its constituent sine-wave frequencies.

basically, you may also have already viewed a device designed to just do that without realizing what it turned into! A graphic equalizer is a bit of high-fidelity stereo equipment that controls (and sometimes shows) the nature of track’s harmonic content material.

geared up with a couple of knobs or slide levers, the equalizer is in a position to selectively attenuate (in the reduction of) the amplitude of definite frequencies present in music, to “customize” the sound for the listener’s advantage. customarily, there should be a “bar graph” reveal next to each manage lever, displaying the amplitude of each and every certain frequency.

Hi-Fi audio graphic equalizer.

hello-Fi audio photo equalizer.

a tool developed strictly to screen—not control—the amplitudes of every frequency range for a mixed-frequency sign is customarily known as a spectrum analyzer.

The design of spectrum analyzers may be so simple as a collection of “filter” circuits (see the next chapter for particulars) designed to separate the distinct frequencies from each and every other, or as complex as a unique-goal digital computing device operating an FFT algorithm to mathematically split the sign into its harmonic accessories.

Spectrum analyzers are often designed to research extraordinarily excessive-frequency indicators, akin to these produced with the aid of radio transmitters and desktop community hardware. In that kind, they often have an appearance like that of an oscilloscope:

Spectrum analyzer shows amplitude as a function of frequency.

Spectrum analyzer shows amplitude as a characteristic of frequency.

Like an oscilloscope, the spectrum analyzer uses a CRT (or a pc screen mimicking a CRT) to monitor a plot of the signal.

in contrast to an oscilloscope, this plot is amplitude over frequency instead of amplitude over time. In essence, a frequency analyzer offers the operator a Bode plot of the signal: anything an engineer could name a frequency-domain in place of a time-area analysis.

The time period “domain” is mathematical: a complicated observe to describe the horizontal axis of a graph. as a consequence, an oscilloscope’s plot of amplitude (vertical) over time (horizontal) is a “time-area” analysis, whereas a spectrum analyzer’s plot of amplitude (vertical) over frequency (horizontal) is a “frequency-domain” evaluation.

after we use SPICE to plot signal amplitude (both voltage or current amplitude) over more than a few frequencies, we're performing frequency-domain evaluation.

Please consider of how the Fourier analysis from the final SPICE simulation isn’t “perfect.” Ideally, the amplitudes of the entire even harmonics may still be absolutely zero, and so should still the DC component. once more, this is now not so a good deal a quirk of SPICE because it is a property of waveforms in general.

A waveform of infinite period (limitless variety of cycles) can be analyzed with absolute precision, but the less cycles available to the desktop for analysis, the much less precise the evaluation. It is only when we now have an equation describing a waveform in its entirety that Fourier analysis can in the reduction of it to a particular collection of sinusoidal waveforms.

the less times that a wave cycles, the less definite its frequency is. Taking this idea to its logical intense, a short pulse—a waveform that doesn’t even complete a cycle—in reality has no frequency, but quite acts as an unlimited latitude of frequencies. This principle is commonplace to all wave-based phenomena, not simply AC voltages and currents.

Suffice it to say that the variety of cycles and the simple task of a waveform’s frequency element(s) are without delay connected.

We could enrich the precision of our analysis here with the aid of letting the wave oscillate on and on for many cycles, and the result can be a spectrum analysis more per the surest. In right here evaluation, I’ve disregarded the waveform plot for brevity’s sake—its just a very long square wave:

square wave v1 1 0 pulse (-1 1 0 .1m .1m 10m 20m) r1 1 0 10k .alternative limpts=1001 .tran 1m 1 .plot tran v(1,0) .4 50 v(1,0) .end fourier accessories of transient response v(1) dc element = 9.999E-03 harmonic frequency fourier normalized part normalized no (hz) part part (deg) part (deg) 1 5.000E+01 1.273E+00 1.000000 -1.800 0.000 2 1.000E+02 1.999E-02 0.015704 86.382 88.182 three 1.500E+02 4.238E-01 0.332897 -5.four hundred -3.600four 2.000E+02 1.997E-02 0.015688 82.764 eighty four.564 5 2.500E+02 2.536E-01 0.199215 -9.000 -7.2 hundred6 three.000E+02 1.994E-02 0.015663 seventy nine.146 eighty.946 7 three.500E+02 1.804E-01 0.141737 -12.600 -10.800 eight four.000E+02 1.989E-02 0.015627 seventy five.529 seventy seven.329 9 four.500E+02 1.396E-01 0.109662 -16.199 -14.399

Improved fourier analysis.

superior fourier evaluation.

note how this evaluation (figure above) suggests much less of a DC element voltage and lower amplitudes for each and every of the even harmonic frequency sine waves, all as a result of we let the desktop pattern greater cycles of the wave. once again, the imprecision of the first evaluation is not so a good deal a flaw in SPICE as it is a fundamental property of waves and of signal evaluation.

overview:

  • square waves are such as a sine wave on the identical (primary) frequency introduced to a limiteless collection of strange-diverse sine-wave harmonics at decreasing amplitudes.
  • laptop algorithms exist that are capable of pattern waveshapes and assess their constituent sinusoidal accessories. The Fourier transform algorithm (primarily the fast Fourier seriously change, or FFT) is accepted in desktop circuit simulation courses akin to SPICE and in digital metering equipment for picking energy excellent.
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